doi: 10.1111/j.1365-2869.2010.00823.x

Sleep restriction for the duration of a work week impairs

multitasking performance

MARJA - LEENA HAAV I STO 1 , 2 , TAR JA PORKKA -HE I SKANEN 3 ,

CHR I STER HUBL IN 1 , M IKKO H ARMA 4 , P ERTT I MUTANEN 5 , K I T I

M ULLER 1 , JU S S I V IRKKALA 1 , 6 and M IKAEL SALL INEN 1 , 7

1Brain and Work Research Centre, Finnish Institute of Occupational Health, Helsinki, Finland, 2Technical Research Centre of Finland, Espoo,

Finland, 3Department of Physiology, Institute of Biomedicine, University of Helsinki, Finland, 4Centre of Expertise Human Factors at Work,

Finnish Institute of Occupational Health, Helsinki, Finland, 5Statistical Services, Finnish Institute of Occupational Health, Helsinki, Finland,6Department of Clinical Neurophysiology, Medical Imaging Centre, Pirkanmaa Hospital District, Tampere, Finland and 7Agora Center,

University of Jyvaskyla, Jyvaskyla, Finland

Accepted in revised form 2 December 2009; received 2 June 2009

SUMMARY It is important to develop shift schedules that minimise the chance for sleep-related

human error in safety-critical domains. Experimental data on the effects of sleep

restriction (SR) play a key role in this development work. In order to provide such data,

we conducted an experiment in which cognitively demanding and long-duration task

performance, simulating task performance at work, was measured under SR and

following recovery. Twenty healthy male volunteers, aged 19–29 years, participated in

the study. Thirteen of them had first two baseline days (8-h sleep opportunity per day),

then five SR days (4-h sleep) and finally two recovery days (8-h sleep). Seven controls

were allowed to sleep for 8 h each night. On each experimental day, multitask

performance was tested in 50-min sessions, physiological sleepiness was evaluated

during multitask performance using electroencephalogram (EEG) ⁄ electrooculogram(EOG) recordings, and psychomotor vigilance task performance and Karolinska

Sleepiness Scale were recorded. Sleep–wake rhythm was monitored throughout the

experiment. The multitask performance progressively deteriorated as a result of

prolongation of the SR and the time spent on the task. The effect was significant at

group level, but individual differences were large: performance was not markedly

deteriorated in all participants. Similar changes were observed also in EEG ⁄EOG-

defined sleepiness. The recovery process of performance and sleepiness from the SR

continued over the two recovery sleep opportunities. In all, our findings emphasise the

importance of shift systems that do not restrict sleep for several consecutive days.

k e y w o r d s cumulative sleep restriction, multitask performance, recovery, sleepiness

INTRODUCTION

In many safety-critical occupations, work consists of multiple

tasks that need to be performed simultaneously. To cope with

these tasks, called multitasks, the workers are required to

switch their attention between subtasks and make decisions on

priorities (Navon and Gopher, 1979; Wickens, 2002; Wickens

et al., 2003). Examples of occupations requiring multitasking

are drivers, pilots, traffic controllers and process operators,

who simultaneously search information from several sources

and have multiple parallel subtasks under processing.

Employees in safety-critical occupations often work under

acute and ⁄or cumulative sleep loss because of irregular and

long work hours (Folkard and Lombardi, 2006; Harma et al.,

2002; Sallinen et al., 2003). The combination of multitasking

and being sleep deprived is potentially hazardous: in trans-

portation and industry, where multitasking is common,

restricted sleep opportunities are a major cause of accidents

Correspondence: Marja-Leena Haavisto, Organisational Psychology,

Technical Research Centre of Finland, P.O. Box 1000, FI-02044 VTT,

Finland. Tel.: +358 40 7056443; fax: +358 20 7225888; e-mail: marja-

leena.haavisto@vtt.fi

J. Sleep Res. (2010) 19, 444–454 Sleep restriction and multitasking

444 � 2010 European Sleep Research Society

(Caldwell, 2005; Philip and Akerstedt, 2006). For example, the

National Transportation Safety Board (NTSB) in the USA has

estimated that fatigue-related accidents involving heavy trucks

make up to 30% of fatal accidents (NTSB, 1990). Previous

research supports the view that restricted sleep markedly

degrades performance in multitasking (Caldwell and Caldwell,

1998; Caldwell and Ramspott, 1998; Elsmore, 1994; Sallinen

et al., 2008). However, from the viewpoint of work life, at least

three important questions have so far been inadequately

addressed by previous research.

The first question concerns cumulative sleep loss, that is,

partial sleep loss across several consecutive days. Until now,

studies of cumulative sleep restriction (SR) have shown that

performance on short duration, usually vigilance tasks grad-

ually degrades in the course of SR (Belenky et al., 2003; Van

Dongen et al., 2003; Webb and Agnew, 1974). Recently it has

been estimated that the extension of wakefulness to >20 h a

day (i.e. < 4 h per night) leads to an escalation of perfor-

mance impairment (McCauley et al., 2009). Although several

studies have addressed multitask performance after acute sleep

loss (Caldwell and Caldwell, 1998; Caldwell and Ramspott,

1998; Elsmore, 1994; Sallinen et al., 2008), to the best of our

knowledge performance after cumulative SR has been

addressed in a single study (Balkin et al., 2004).

Second, in many safety-critical occupations performance

needs to be maintained at a high level for long periods of time

uninterrupted. The time-on-task effect, that is, a progressive

deterioration of performance in the course of the task session,

is affected by SR (Dinges and Kribbs, 1991). Thus, it can be

argued that the duration of the task may be a critical factor in

occupational safety. Until now, the time-on-task effect on

multitasking has been studied in two acute sleep deprivation

studies. In one of these studies, the time-on-task effect was

markedly increased after the first 10 min on the task (Caldwell

and Ramspott, 1998), whereas in the other the effect just

approached significance in a 70-min test session (Sallinen

et al., 2008). Studies on the time-on-task effect on multitasking

under cumulative SR are lacking.

The third understudied question regards recovery from

partial cumulative sleep loss. This information is crucial when

planning shift work schedules; particularly when considering

the number of days off between two consecutive shift spells.

Until now, recovery of multitasking performance has been

examined in one study showing that 8-h sleep after 1 night of

partial sleep loss is not sufficient for full recovery (Sallinen

et al., 2008). Recently, Banks et al. (2007) and McCauley et al.

(2009) have shown that a single recovery night of extended

sleep after cumulative SR improves participants� performance,

but leaves their vulnerability to sleep deprivation at an

elevated level. The pace of recovery after SR is affected by at

least two determinants: the first of which is severity of SR – the

more severe the sleep loss, the longer the period of recovery

required (Lamond et al., 2007); the second element is the

nature of sleep loss – recovery from cumulative sleep loss

appears to require more time than recovery from acute sleep

loss (Axelsson et al., 2008; Belenky et al., 2003; Lamond et al.,

2007). In addition, the methods used to measure the recovery

process matter, for example, the recovery of subjective

sleepiness occurs earlier than the recovery of physiological

sleepiness (Lamond et al., 2007). With this in mind, there is a

clear need to ascertain how multitasking performance recovers

from cumulative sleep loss.

This study was aimed at elucidating the three above-

mentioned practical questions. We hypothesised that cumula-

tive sleep loss, reflecting a restriction of sleep for duration of a

work week, leads to progressive impairments in multitasking.

We predicted that the degree of impairment would be affected

by both the duration of the task (the time-on-task effect) and

the number of days of restricted sleep (extent of sleep loss). We

were also interested in the recovery process, and posed the

question whether 2 days, simulating a weekend, are sufficient

for recovery of a multitask performance of long duration. We

curtailed young male volunteers� sleep opportunity for 5 days,

and thereafter allowed them to sleep normally for 2 nights

while measuring their multitask performance in two 50-min

sessions every day. To examine the overall effect of the SR and

the recovery days, we also measured participants� subjective,behavioural and physiological sleepiness in the course of the

experiment. The results from the SR group were compared

with those from a group that was offered a sleep opportunity

of 8 h each night through the experiment.

MATERIALS AND METHODS

Participants

After signing a form for informed consent, 20 healthy men

(aged 19–29 years) with 7–9 h of habitual sleep and sleep need

voluntarily participated in the study. The measure of habitual

sleep need was based on participant�s subjective evaluation in

the questionnaire. The Ethics Committee of the Hospital

District of Helsinki and Uusimaa approved the study. Prior to

the study, participants were screened to exclude those with

extreme circadian types, sleep disorders, psychiatric illness,

chronic or recent acute medical conditions, a history of drug or

alcohol dependence, having crossed time zones during 4 weeks

preceding the beginning of the study, habitual napping, and

shift work and ⁄or night work. Positive criteria for selection

included regular lifestyles with habitual bedtime before

24:00 hours and wake-up time after 06:00 hours. The Nordic

Sleep Questionnaire (Partinen and Gislason, 1995), medical

screening questionnaires, and clinical blood and urine labora-

tory tests were used to identify and exclude individuals with

drug dependence, sleep disorders and other conditions. In the

second phase, the participants were examined by a physician to

ensure fitness for the experiment.

Procedures prior to the experiment

At least 2 weeks before the experiment, the participants

slept an adaptation night in the laboratory, and a polysomn-

ogram, including electroencephalography (EEG), bilateral

Sleep restriction and multitasking 445

� 2010 European Sleep Research Society, J. Sleep Res., 19, 444–454

electrooculography (EOG), submental electromyography and

electrocardiography, was recorded to exclude persons suffering

from organic sleep disorders.

The participants were instructed to maintain a regular sleep–

wake cycle for 2 weeks prior to the study, which was verified by

wrist-worn actigraphy and sleep diary recordings. In addition,

they were instructed to maintain a regular nutrition schedule,

and to refrain from caffeine, alcohol and tobacco for 2 weeks

before arriving in the sleep laboratory. Mean sleep duration

was 6 h 53 min (SD = 35.0 min) in the SR group and 7 h

(SD = 51.4 min) in the control group during the 14 days

preceding the experiment derived from actigraphy data.

Design and experimental procedures

Participants were randomly selected to the experimental or

control groups. Participants spent 10.5 consecutive days in the

laboratory (Fig. 1). The first day was an adaptation ⁄ trainingday (A) and the second served as baseline (BL). During A,

participants became familiar with the day schedule, and

practised the tasks and self-rating scales. Thirteen of the

participants underwent sleep deprivation conditions, including

the training and baseline day (8 h in bed per night, 23:00–

07:00 hours), 5 days of partial sleep loss (4 h in bed per night,

03:00–07:00 hours), and two recovery days (8 h in bed per

night, 23:00–07:00 hours). The remaining seven volunteers

were allowed to sleep for 8 h per night throughout the

experiment.

No alcohol, tobacco or caffeine was allowed during the

laboratory visit. The fixed meal hours and amount of calories

per meal were as follows: breakfast 600 kcal at 07:30 hours;

lunch 800 kcal at 12:30 hours; snack 300 kcal at 15:30 hours;

dinner 700 kcal at 18:00 hours; and snack 200 kcal at

21:30 hours. The participants were under behavioural moni-

toring, and their sleepiness was measured by EEG and EOG

24 h per day.

The study was designed to simulate a typical work week with

daily working time between 07:00 and 16:30 hours. The

participants completed a 50-min multitask session at 10:00,

11:40 and 14:00 hours on each of the 9 days. One of the two

forenoon sessions contained a 10-min rest pause, and the data

from this session were not included in this study. The

scheduling of the forenoon multitask sessions with and without

the 10-min break was counterbalanced across the days and

participants. To avoid the knowledge-of-results effect, the

participants were not provided with feedback from their

performance during the experimental days.

The psychomotor vigilance task performance (PVT) was

administrated each day at 07:10, 11:00 and 15:00 hours. The

Karolinska Sleepiness Scale (KSS) was rated at the beginning

and end of each multitask session. Each time, two participants

belonging to the same group spent the night at the laboratory

at the same time. Between the task sessions, participants were

allowed to read, watch TV or movies, and interact with each

other and the laboratory staff helped them to stay awake. In

order to avoid light exposure, going outdoors was not

permitted. In addition, physical exercise was not allowed

during the laboratory experiment. Illumination in the sleeping

room and in the test room ranged from 150 to 400 lux, and in

the living room from 350 to 600 lux. The temperature ranged

from 19 to 23 �C.

EEG recording

Electroencephalogram was recorded from 10 to 20 system

derivations Fp1-A2, Fp2-A1, C3-A2, C4-A1, O1-A2 and O2-

A1. The recordings were conducted with a digital recorder

(Embla, Flaga HF, Reykjavik, Iceland), using a sampling rate

of 200 Hz with a bandwidth of 0.5–90 Hz. Electrode imped-

ances were checked and corrected at the beginning of each

recording. The sleep periods were visually scored and classified

in 30-s epochs into sleep stages according to the criteria of

Rechtschaffen and Kales (1968).

EOG ⁄EEG-defined sleepiness

The daytime EEG and EOG data were recorded from the same

locations and at the same sampling rate as in the night

measurements. The EEG and EOG recordings during the

multitask sessions were scored into the following four catego-

ries in 20-s epochs: (1) wakefulness; (2) drowsiness indicated by

slow eye movements accompanied by theta activity of < 5 s

period in EEG; (3) microsleep indicated by theta activity for

5–10 s in EEG; and (4) stage 1 sleep indicated by theta activity

for at least a 10-s period in EEG (Sallinen et al., 2004, 2008).

All categories but category 1 were defined as increased

sleepiness during multitasking. The data of EOG ⁄EEG-

defined sleepiness and multitask performance from each

Figure 1. Study experimental design, showing nightly time in bed

across days: adaptation (A), baseline (BL), sleep restriction days (SR1–

SR5) and recovery (R1–R2), and measurements of psychomotor vig-

ilance task performance (PVT) and multitasking in the 4-h SR group.

Karolinska Sleepiness Scale (KSS) ratings were collected at the

beginning and end of each task session. The control group had a

similar schedule, with the exception that they had the opportunity to

sleep 8 h per night throughout the study. One of the two forenoon

sessions contained a 10-min break, and the data collected during this

session have been excluded from this study.

446 M.-L. Haavisto et al.

� 2010 European Sleep Research Society, J. Sleep Res., 19, 444–454

50-min task session were divided into five 10-min segments for

illustrations and statistical analyses.

Performance measures

Multitasking

A computerised multitask entitled Brain@Work (see Fig. 2)

consisting of four subtasks was developed at the Finnish

Institute of Occupational Health. It represents a modified

version of a multitask entitled SYNWORK that has been

previously used in sleep deprivation studies and found to be

sensitive (Caldwell and Caldwell, 1997; Caldwell and Ram-

spott, 1998; Elsmore, 1994). The four subtasks of the multitask

are introduced at scheduled intervals, and the participant must

be able to choose the optimal moment for the performance of

each subtask. The Brain@Work has been employed in our

recent acute sleep deprivation study in a similar manner as in

this study (Sallinen et al., 2008).

In the short-term memory subtask, at the beginning of each

task session for a period of 10 s the participants were shown a

string of target letters that they were instructed to learn.

During the test sessions, the participants were presented with

probe letters one at a time at 7-s intervals. The participants�task was to classify each probe letter as either a target or a

non-target by clicking on the icons �Yes� or �No�.In the arithmetic subtask, the instruction was to indicate the

sum of two numbers by clicking on digits on a digit pad on the

computer screen. The duration of each trial was 7 s. In short-

term memory and arithmetic subtasks, the participants

obtained 10 points for each correct response, )10 points for

each false response, and )20 points for not responding before

stimulus offset.

In the visual monitoring subtask, participants were

instructed to return a moving dot to the centre of the

innermost circle by clicking on the �Reset� icon. The number

of points obtained (2, 4, 6 or 10) was greater the nearer the dot

was to the outermost edge upon responding. If the participant

did not react before the dot reached the outmost circle, which

took 10 s, 10 points were deducted per each elapsed second. In

the auditory monitoring, the participants were instructed to

discriminate between a non-target tone of 1000 Hz (80%

probability) and a target tone of 1200 Hz (20% probability).

The tones (intensity 62 dB SPL, duration 50 ms) were

presented at 1.5-s intervals. The participants were instructed

to press �Enter� whenever they heard the target tone. The

points were awarded and subtracted identically for the

memory and arithmetic subtasks.

Less than 2 weeks before the experiment, each participant

practised the multitask for 30 min. The level of difficulty in the

task was defined individually for the experiment (see below).

This procedure made it possible to set task difficulty equally

according to each participant�s capacity. The participants

performed the multitask for an average duration of 75 min

(SD = 23.3 min) in the SR group and for 74 min (SD = 55.5

min) on average in the control group during the performance

level adjustment procedure. In all, the participants practised

the multitask for an average of 105 min prior to the experi-

ment to flatten the practice effect. Moreover, on the first day of

the experiment (Day A in Fig. 1), the participants practised the

multitask for 140 min.

To achieve comparable task difficulty between individuals,

difficulty level was determined in two phases. First, the

difficulty levels of the short-term memory and mental arith-

metic subtasks were defined. With this procedure, the effects of

individual differences on the performance of individual tasks

could be controlled for (Baddeley et al., 1997). In the short-

term memory subtask, the number of the target letters was set

two letters shorter than the smallest number of letters that the

participant failed twice to repeat. In the arithmetic subtask, the

number of digits was one less than the smallest number of

digits found too difficult for the participant in the additions

task (<80% of the additions correct). Second, the temporal

intensity of the arithmetic and short-term memory subtasks

was adjusted by manipulating the inter-stimulus interval (ISI,

i.e. the time between two successive items) in 5-min multitask-

ing sessions. In the first 5-min session, the ISI was 6.5 s, and it

was shortened by 0.5 s per session all the way down to 0.5 s if

needed. The adjustment of temporal intensity was finished

when the participant failed to obtain at least 70% of the total

score twice.

Vigilance

A 10-min PVT was used to evaluate behavioural alertness

(Dinges and Powell, 1985). During this task, the participants

were instructed to attend to the timer presented on the

computer screen and press the response button as quickly as

possible whenever the timer started running. The ISI varied

from 2000 to 10 000 ms. The mean number of lapses [reaction

times (RTs) longer than 500 ms] and the slowest 10% of all

responses (mean 1 ⁄RT · 1000 from slowest 10% RTs per

trial) were used as dependent measures.Figure 2. A computer screen showing the four subtasks of the

Brain@Work multitask.

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Subjective measures

Subjective sleepiness was measured using the nine-point KSS

(Akerstedt and Gillberg, 1990). The scale varies from very alert

(1) to very sleepy ⁄fighting sleep ⁄ effort to keep awake (9).

Statistical analysis

Statistical analyses were performed using linear mixed-model

anovas, as this technique is suited for the analysis of individual

differences over time (Bliese et al., 2006; Van Dongen et al.,

2003). Traditional repeated-measures anova are inappropriate

for distinguishing stable changes from error variance across

measurement points. Moreover, repeated-measures anovas

assume equal variances within each group. Our mixed-models

included group (SR, control) and day (BL, SR1, SR2, SR3,

SR4, SR5, R1, R2) as fixed effects, and time-on-task (1st, 2nd,

3rd, 4th, 5th 10-min multitask interval) as a random effect.

Separate analyses were performed to test the effects of the SR

days (days BL, SR1, SR2, SR3, SR4 and SR5) and the

recovery days (days BL, R1, R2) on the dependent variables.

The time-of-day factor was left out of the models, as

preliminary analysis showed no difference between the fore-

noon and the afternoon sessions. A random effect on the

intercept and random slopes for centred (to the value of 3rd

10-min segment in each 50-min task session) multitask score or

percentage of EEG ⁄EOG-defined sleepiness was included in

the models to account for individual differences in the

dependent variables. For intraclass correlation (ICC) calcula-

tions, we used only random intercept models without random

slope of the time-on-task factor. In analysis we extended the

compound symmetry correlation structure for the repeated

observations using the linear covariance structure parameter

(PARM) of the SAS ⁄MIXED-procedure to account for the

different correlations during measurements in the same day

and between the different days. The data were analysed using

PROC MIXED in SAS 9.1 (Sas Institute Inc., 2004).

An ICC for multitask performance was computed from the

estimated between-subjects variance (systematic interindividu-

al variance) and the within-subjects variance (residual intra-

individual variance) separately for the experimental and the

control group. These variance components analyses were

performed by mixed-model anova, with day as a fixed linear

effect (five SR days) and participants as a random effect

(random intercept model). Confidence limits for ICC were

calculated with SAS ⁄NLMIXED procedure by the estimate

statement where the limits are based on the t-distribution

rather than on the standard normal distribution.

RESULTS

Sleep length in the experiment

Mean sleep duration for the different days of the experiment in

the SR and the control group are given in Fig. 3. It shows that

the experimental manipulation of sleep opportunities resulted

in the planned changes in sleep duration. In the SR group, the

mean sleep length was 7 h 19 min (SD = 17.4 min) on the

baseline night, reduced to 3 h 52 min (SD = 2.4 min) on

the SR days, and returned to baseline level (7 h 40 min,

SD = 8.3 min) in the recovery phase. The SR group slept, on

average, 47.2% less on the SR nights than at baseline. The

control group slept, on average, 7 h 20 min (SD = 13.4 min)

per night without marked variation between the nights.

Effects of restricted sleep

All results of mixed-model anovas are presented in Table 1.

Multitask performance

In the SR group, multitask performance was gradually

impaired over the SR days compared with the control group

(P < 0.0001; Fig. 4a). Also the group · day · time-on-task

interaction was significant (P < 0.0001), meaning that the

deterioration of performance in the task sessions progressed

more steeply in the SR group than in the control group over

the SR days.

Figure 4b displays a predicted average line for multitask

performance (time-on-task as a random effect). Each SR day

the slope for the daily parameter estimates (group · day ·time-on-task) was steeper in the SR group (from the baseline

estimate = 19.20, t = 0.65, P = 0.5150 to the fifth SR day

estimate = )205.80, t = )6.98, P < 0.0001) compared with

those of the controls (from the baseline estimate = 9.22,

t = 0.23, P = 0.8185 to the fifth SR day estimate = 4.16,

t = 0.10, P = 0.9176). Fig. 5 presents examples of individuals

who performed at high, middle and low level during the SR

days. In two individuals performance deteriorated >80%

from the baseline level and in four individuals maximally only

Figure 3. Mean (and SEM) total daily sleep durations in hours in the

sleep restriction group (SR) and control group. Error bars are included

but are obscured by data points. BL, baseline; R, recovery.

448 M.-L. Haavisto et al.

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7%; in the rest of the individuals the performance deteriora-

tion was in-between the two extremes.

An ICC indicated that the order between the participants in

multitasking remained substantially stable in the control group

[ICC = 96.0%, 95% confidence interval (CI) = 89.4–100,

between-subject variance = 2129113, SE = 1148545, t =

1.85, P = 0.1132 and within-subject variance = 98386, SE =

26295, t = 3.74, P = 0.0096], but also in the SR group

(ICC = 81.4%, 95% CI = 66.2–96.5, between-subject vari-

ance = 7865102, SE = 3227152, t = 2.44, P = 0.0313 and

within-subject variance = 1802889, SE = 353576, t = 5.10,

P = 0.0003) during the SR days.

EEG ⁄EOG-defined sleepiness while multitasking

A significant group · day · time-on-task interaction (P =

0.0004) revealed that the groups differed in terms of how much

EEG ⁄EOG-defined sleepiness increased within the 50-min

multitask sessions during the SR days. Figure 6 shows that the

time-on-task effect increased more for the SR group than the

control group as the number of days increased. There were

only two individuals whose EEG ⁄EOG-defined sleepiness

Table 1 Results of mixed-model anovas for the main and interaction

effects of group, day and time-on-task on multitasking, EEG ⁄EOG-

defined sleepiness, subjective sleepiness (KSS) and vigilance per-

formance (PVT)

Measure df F-value P-value

Sleep restriction days

Multitasking

Group 1,1157 2.67 0.1024

Day 5,1157 2.34 0.0395

Time-on-task 1,18 5.14 0.0359

G · D 5,1157 6.27 <0.0001

G · T 1,1157 6.68 0.0099

D · T 5,1157 6.27 <0.0001

G · D · T 5,1157 8.40 <0.0001

EEG ⁄EOG-defined sleepiness during multitasking

Group 1,1157 2.81 0.0937

Day 5,1157 1.74 0.1216

Time-on-task 1,18 2.27 0.1492

G · D 5,1157 1.81 0.1089

G · T 1,1157 2.49 0.1146

D · T 5,1157 3.91 0.0016

G · D · T 5,1157 4.62 0.0004

KSS

Group 1,18 2.75 0.1143

Day 5,90 7.87 <0.0001

G · D 5,90 4.90 0.0005

PVT lapses

Group 1,18 3.02 0.0995

Day 5,90 2.74 0.0238

G · D 5,90 2.56 0.0327

Recovery days

Multitasking

Group 1,569 1.16 0.2817

Day 2,569 1.04 0.3530

Time-on-task 1,18 0.02 0.8997

G · D 2,569 4.12 0.0168

G · T 1,569 1.22 0.2697

D · T 1,569 2.77 0.0634

G · D · T 2,569 2.73 0.0659

EEG ⁄EOG-defined sleepiness during multitasking

Group 1,569 0.17 0.6845

Day 2,569 0.94 0.3928

Time-on-task 1,18 2.24 0.1515

G · D 2,569 2.37 0.0947

G · T 1569 4.12 0.0430

D · T 2,569 2.73 0.0659

G · D · T 2,569 4.19 0.0157

KSS

Group 1,18 0.10 0.7555

Day 2,36 1.68 0.2012

G · D 2,36 0.18 0.8371

PVT lapses

Group 1,18 0.64 0.4328

Day 2,36 0.97 0.3899

G · D 2,36 0.28 0.7569

D, day; EEG, electroencephalogram; EOG, electrooculogram; G,

group; KSS, Karolinska Sleepiness Scale; PVT, psychomotor

vigilance task performance; T, time-on-task.

A BL SR1 SR2 SR3 SR4 SR5 R1 R2600800

100012001400160018002000220024002600

SR Control

Tota

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tita

sk s

core

Day

A BL SR1 SR2 SR3 SR4 SR5 R1 R2

600800

100012001400160018002000220024002600

Tota

l mul

tita

sk s

core

Day

SR Control

(a)

(b)

Figure 4. (a) Mean (and SEM) total score in 50-min multitask per-

formance at 10-min intervals over the experimental days. The daily

means of two 50-min sessions are presented in the sleep restriction

group (SR) and the control group. (b) Predicted average multitask

score for the SR group and the control group. BL, baseline; R,

recovery.

Sleep restriction and multitasking 449

� 2010 European Sleep Research Society, J. Sleep Res., 19, 444–454

increased 25% or more from the baseline to the fifth SR day.

Noteworthy, these were the same individuals whose perfor-

mance deteriorated at least 80% during the SR. The other

individuals in the SR group showed only an increase of 0–6%

change in physiological sleepiness during multitasking.

PVT

The number of PVT lapses increased more in the SR group

than in the control group (P = 0.0327; Fig. 7). The estimated

number of lapses increased from 0.92 ± 0.73 (BL) to

3.54 ± 0.73 (SR5) in the SR group, and from 0.62 ± 1.00

to 0.90 ± 1.00 in the control group. There was a tendency that

the slowest 10% of all the responses were slower in the SR

group, but the group difference was not statistically significant

(P = 0.16).

Subjective sleepiness

Self-rated sleepiness increased more in the SR group than in

the controls after the baseline day (P = 0.0005; Fig. 8). The

estimated ratings of sleepiness (KSS) during the SR days

increased from 4.65 ± 0.29 (BL) to 6.2 ± 0.29 (SR5) in the

SR group, and from 4.9 ± 0.39 to 5.0 ± 0.39 in the control

group.

Effects of recovery sleep

Multitask performance

Figure 4a shows that the multitask performance in the SR

group improved close to the level of the controls following the

first recovery sleep and that the group difference diminished

further following the second recovery sleep. A significant

A BL SR1 SR2 SR3 SR4 SR5 R1 R20

2

4

6

8

10

12

14

16

EE

G/E

OG

-def

ined

sle

epin

ess

(

)

Day

SR Control

Figure 6. Mean (and SEM) electroencephalogram (EEG) ⁄ electrooc-ulogram (EOG)-defined sleepiness at 10-min intervals during the

multitask sessions over the experimental days. The daily means of

forenoon and afternoon sessions are presented in the sleep restriction

group (SR) and the control group. BL, baseline; R, recovery.

A BL SR1 SR2 SR3 SR4 SR5 R1 R2

–1500

–1000

–500

0

500

1000

1500

2000

2500

Tot

al m

ulti

task

sco

re

Day

High performance Middle Low performance

Figure 5. Total multitask performance scores at 10-min intervals for

three individuals of the sleep restriction (SR) group whose perfor-

mance either markedly (low performance), moderately (middle) or

only slightly (high performance) impaired during the experimental

days. BL, baseline; R, recovery.

Figure 7. Mean number (and SEM) of lapses per day in the PVT in the

sleep restriction group (SR) and the control group. BL, baseline; R,

recovery.

A BL SR1 SR2 SR3 SR4 SR5 R1 R21

2

3

4

5

6

7

8

9 SRControl

KSS

Day

Figure 8. Mean daily ratings (and SEM) of subjective sleepiness

(Karolinska Sleepiness Scale, KSS) for the sleep restriction group (SR)

and the control group. The mean values represent KSS ratings col-

lected before and after the multitask sessions in the forenoon and

afternoon. BL, baseline; R, recovery.

450 M.-L. Haavisto et al.

� 2010 European Sleep Research Society, J. Sleep Res., 19, 444–454

group · day interaction (P = 0.0168) indicated that the

recovery process continued still during the second night of

recovery. The daily parameter estimates for time-on-task lines

decreased from R1 (estimate = )37.63, t = )3.09, P =

0.0021) to R2 (estimate = )3.61, t = )0.30, P = 0.7673) in

the SR group, meaning that the time-on-task effect almost

disappeared during R2. The control group showed no com-

parable changes.

EEG ⁄EOG-defined sleepiness while multitasking

A significant group · time-on-task · day interaction

(P = 0.0157) demonstrated that the difference between the

groups in physiological sleepiness was dependent on both the

time spent on the task and the number of recovery days.

Figure 6 shows that the group difference in the time-on-task

effect decreased from R1 to R2.

PVT

The groups did not differ in the number of PVT lapses during

the recovery period.

Subjective sleepiness

The sleepiness ratings on the recovery days showed no group

differences.

DISCUSSION

The main findings of this study were that at a group level

multitask performance was significantly impaired by 5 days of

partial SR, and that this impairment increased as a function of

the time spent on the task. However, within the group exposed

to the SR, only few individuals showed large impairments in

their performance. Most of the sleep-deprived individuals

showed only moderate deteriorations and some individuals�performance remained virtually unchanged. In addition,

EEG ⁄EOG-defined sleepiness increased significantly at the

group level during multitasking in the course of the SR but,

actually, there were only few individuals whose sleepiness

increased markedly.

The finding that multitask performance progressively dete-

riorated with the increasing number of SR days is in line with

previous studies in which participants� performance on less

complicated and shorter tasks deteriorated in the course of SR

(Belenky et al., 2003; Dinges et al., 1997; Van Dongen et al.,

2003). From the viewpoint of work life, the strength of this

study was that the used task included two important charac-

teristics of real operational tasks that are often performed

under SR, namely high demands on cognitive processes such as

divided attention (Gopher, 1996; Wickens et al., 2003) and the

requirement of performance over long periods. In practice, our

finding can be understood that a high number of sleep-limiting

shifts in a row substantially increase the risk for human error

in operational tasks that require multitasking. However,

studies conducted in authentic work conditions are needed to

verify this conclusion, as, for example, expertise based on long

experience and awareness of the consequences of a perfor-

mance error probably also play a role in how well a person

actually performs at work while restricted of sleep.

The progressively augmenting time-on-task effect on multi-

task performance was observed in the SR but not in the

control group, indicating that it was totally dependent on the

sleep loss preceding the performance. The time-on-task effect

on multitasking or simulator performance has been also found

in previous studies on acute sleep loss (Akerstedt et al., 2005;

Caldwell and Ramspott, 1998; Sallinen et al., 2008). The

practical significance of this finding is high. In safety-critical

occupations, for example, with air-traffic controllers, most task

sessions performed under sleep loss are relatively long in

duration. Interrupting the working period with a break could

theoretically be of advantage. However, our previous work has

shown that it is unlikely that, for example, a rest pause with

light neck-and-shoulder exercise would be an effective remedy

(Sallinen et al., 2008). Cognitive performance during SR is, to

some extent, improved by napping (Mollicone et al., 2008;

Purnell et al., 2002; Sallinen et al., 1998), and thus naps during

breaks could be of advantage. Another strategy is to use

stimulants. However, continuous use often leads to tolerance

and increased dosages, which may affect sleep following the

shift.

The time-on-task effect on multitasking intensified in the

course of the SR. Previous studies have shown that 20 h of

wakefulness per day – the same amount that was used in this

study – is sufficient for escalation of performance impairments

(McCauley et al., 2009). Our new finding was that most of the

deterioration occurred during the latter part of the 50-min task

session, implying that the escalating negative effects of

extended wakefulness on multitask performance are dependent

on the time spent on the task.

There are various brain mechanisms that may explain the

observed deterioration in multitasking. The increases in

EEG ⁄EOG-defined sleepiness during the deterioration of

multitasking suggest that at least the arousal mechanisms

played a key role. The level of thalamic activation that

regulates arousal and attention has been found to decrease in

association with sleep deprivation (Chee et al., 2006, 2008;

Coull et al., 1998; Thomas et al., 2000). This deactivation

could at least to some extent explain the observed decrements

in multitask performance under SR. On the contrary, multi-

tasking places special demands on cognitive processes required

in subtasks and coordinating attention switching between the

subtasks (D�esposito et al., 1995; Dux et al., 2006; Just et al.,

2001, 2008). SR-induced changes in brain mechanisms under-

lying these cognitive processes may thus also explain the

observed deterioration in multitasking.

Large individual differences in multitasking were observed

on the SR days. Importantly, the individual differences were

substantially stable within this period: the same individuals

showed either sensitivity or tolerance to the curtailment of

sleep. Only two individuals out of 13 exhibited severe

Sleep restriction and multitasking 451

� 2010 European Sleep Research Society, J. Sleep Res., 19, 444–454

decrements in multitask performance and, interestingly, the

same individuals also showed the most severe increase in

EEG ⁄EOG-defined sleepiness during the task performance.

Our finding of large individual differences in multitasking

within a single SR period is in line with a study by Van Dongen

et al. (2006) in pilots. In their study, differences in flight-

simulator performance between sleep-deprived pilots were

large and stable in the course of a single experiment (Van

Dongen et al., 2006).

The individual differences observed in this study cannot be

explained by differences in cognitive aptitude. Prior to the

experiment, the cognitive demand of the task was adjusted

individually to be 70% of the maximal capacity of each

participant. The individual adjustment was carried out because

previous studies have shown that the ability to divide attention

between one or more simultaneous tasks differs greatly from

one person to another (Damos, 1993). The adjustment

protocol ensured that all individuals were able to perform

the multitask and that the starting level for each individual was

equally demanding. The observed differences suggest that there

are individual differences in tolerance for SR (Leproult et al.,

2003; Van Dongen et al., 2003, 2004). In our study, individual

differences remained stabile through the SR days, but we did

not examine whether the differences would have been replica-

ble in a repeated exposure to SR.

It is not self-evident how and to what extent the individual

differences in response to sleep loss should be accounted for in

shift work: whether they should be used as a selection criterion

when recruiting new personnel or whether they should be used

as a basis for adjusting work demands, including working

hours, on an individual basis. The seriousness of the safety

hazard associated with the task in question is one aspect to be

considered in this context. Second, it would be important to

establish the possibilities for obtaining reliable data on a

person�s sensitivity to sleep deprivation before starting shift

work. For the moment, it seems that the only reliable way of

indentifying persons with high vulnerability to sleep loss is to

subject them to such conditions, as no potential baseline

predictor has turned out to be reliable enough for this purpose

(Van Dongen and Belenky, 2009). In addition, a Bayesian

forecasting technique based on closed-loop feedback of mea-

sured performance can be used for predicting changes in a

sleep-deprived worker�s job performance (Van Dongen and

Belenky, 2009).

Electroencephalogram ⁄ electrooculogram-defined sleepiness

during multitasking responded to SR similarly to multitask

performance itself: sleepiness increased as a function of the

time spent on the task and the number of SR days, but actually

only two individuals out of 13 showed a marked increase.

Previous studies have found no clear associations between

changes in cognitive performance and concomitant physiolog-

ical sleepiness under sleep loss (Galliaud et al., 2008; Stenuit

and Kerkhofs, 2008; Wilson et al., 2007). This may be partly

due to the different durations of tasks used in the previous

studies: in this study, the task duration was much longer than

those used earlier. It can be assumed that the association is

more obvious when the effect of sleep loss on both measures

has augmented close to its maximum at the end of the task

performance. In all, our findings suggest that increased

physiological sleepiness is at least one of the factors underlying

impaired long-duration multitasking under cumulative sleep

loss.

Both standard measures of sleepiness, the KSS ratings and

number of PVT lapses, were affected by the SR. On the fifth

SR day, the mean level of the KSS ratings was close to the level

(‡7) that is known to be associated with electrophysiological

signs of extreme sleepiness and impaired driving performance

(Akerstedt and Gillberg, 1990; Ingre et al., 2006). A somewhat

surprising result was that the slowest 10% of the PVT response

times were not significantly affected by the SR. A reason for

this result may be that the PVT was always presented

immediately after a long-duration multitask session. This

protocol may have affected the level of arousal at which the

PVT task was initiated.

Recovery of long-duration multitasking from the cumulative

SR proceeded gradually. Following the first recovery sleep

period, the level of performance clearly improved as compared

with the last SR day, but still remained below that of the

control group. Performance returned to the baseline level after

the second recovery sleep period. In the course of the gradual

recovery process, the time-on-task effect and individual differ-

ences decreased. In a previous study, full recovery from a

7-day SR was not reached after three recovery nights (Belenky

et al., 2003). Interestingly, extension of sleep duration for

several days previous to SR improved the rate of performance

recovery (Rupp et al., 2009). The relationship between the

severity of the preceding SR (accumulated sleep loss) and

the pace of recovery process warrants further research. The

question is of practical significance when planning shift work

schedules: how many recovery days must be included in the

schedule after a certain number of sleep-limiting shifts?

The recovery process of EEG ⁄EOG-defined sleepiness

during multitasking resembled that of multitask performance:

the recovery process continued over the two recovery sleep

opportunities and was characterised by decreases in the time-

on-task effect and in individual differences. This finding is in

line with our recent study, where both long-duration multitask

performance and EEG ⁄EOG-defined sleepiness responded

similarly to an 8-h sleep opportunity after only 2 h of sleep

on the previous night (Sallinen et al., 2008). When considering

time, needed for recovery, it is important to notice that the

participants of this study were provided with optimal sleeping

conditions free from many sleep-disturbing factors normally

present in everyday life. Thus, it is possible that recovery takes

even longer under real working conditions than in our

laboratory environment.

There are several limitations in our study that should be

taken into account to interpret the results. First, our sample

consisted of only young healthy men, which limits the

possibilities to generalise the results to other age groups,

women, persons with health problems, and experienced shift

workers. Second, the long-term stability of the observed

452 M.-L. Haavisto et al.

� 2010 European Sleep Research Society, J. Sleep Res., 19, 444–454

individual differences in response to SR remains open, as the

participants were exposed to SR only once. Third, the recovery

process from 5 days of SR was followed only for 2 days.

However, shift schedules often contain repetitive spells of

sleep-limiting shifts with only a day or two off between them.

In this context, the question of how many recovery days is

needed to prevent any carry-over effect from a period of SR to

the next one is of importance, but cannot be answered on the

basis of our results. Finally, the laboratory conditions of our

study limit the possibilities to generalise the results to everyday

life and thus field studies are needed to verify our findings.

CONCLUSIONS

In conclusion, this study demonstrates that complex and long-

duration cognitive performance gradually degrades in young

healthy men when their sleep is restricted to 4 h per night for

5 days. This degradation is characterised by a strong time-on-

task effect and large individual differences, and accompanied

with an increase in physiological sleepiness. Recovery from

restricting sleep to 4 h per night for a period of a work week

takes at least two 8-h sleep opportunities.

ACKNOWLEDGEMENTS

This study was supported by the European co-funded, 6th

FW, Integrated project SENSATION (IST, 507231), Finnish

Work Environmental Found and National Technology

Agency of Finland. We would like to thank Outi Fischer,

Hannele Huhta, Seija Karas, Hannele Kataja, Nina

Lapvetelainen, Mari Marjamaki, Johanna Parikka, Teppo

Valtonen, Riitta Velin and students from the medical faculty

of Helsinki University for invaluable assistance in recruiting

and screening of the participants, and running of the

experiments. We would also like to thank Jaana Hiltunen,

Kati Hirvonen, Anu Holm and Mika Letonsaari for technical

help in this study. In addition, we received generous help and

important comments from Risto Nasanen, PhD, and Ritva

Akila, neuropsychologist.

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